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第八章 学术篇
论文下载： 链接：https://pan.baidu.com/s/1G-WFCzAU2VdrrsHqJzjGpw 密码：vhfw
- 8.1 The Geometry of Innocent Flesh on the Bone: Return-into-libc without Function Calls (on the x86)
- 8.2 Return-Oriented Programming without Returns
- 8.3 Return-Oriented Rootkits: Bypassing Kernel Code Integrity Protection Mechanisms
- 8.4 ROPdefender: A Detection Tool to Defend Against Return-Oriented Programming Attacks
- 8.5 Data-Oriented Programming: On the Expressiveness of Non-Control Data Attacks
- 8.6 Hacking Blind
- 8.7 What Cannot Be Read, Cannot Be Leveraged? Revisiting Assumptions of JIT-ROP Defenses
- 8.8 All You Ever Wanted to Know About Dynamic Taint Analysis and Forward Symbolic Execution (but might have been afraid to ask)
- 8.9 Symbolic Execution for Software Testing: Three Decades Later
- 8.10 AEG: Automatic Exploit Generation
- 8.11 Address Space Layout Permutation (ASLP): Towards Fine-Grained Randomization of Commodity Software
- 8.12 ASLR on the Line: Practical Cache Attacks on the MMU
- 8.13 New Frontiers of Reverse Engineering
- 8.14 Who Allocated My Memory? Detecting Custom Memory Allocators in C Binaries
- 8.15 EMULATOR vs REAL PHONE: Android Malware Detection Using Machine Learning
- 8.16 DynaLog: An automated dynamic analysis framework for characterizing Android applications
- 8.17 A Static Android Malware Detection Based on Actual Used Permissions Combination and API Calls
- 8.18 MaMaDroid: Detecting Android malware by building Markov chains of behavioral models
- 8.19 DroidNative: Semantic-Based Detection of Android Native Code Malware
- 8.20 DroidAnalytics: A Signature Based Analytic System to Collect, Extract, Analyze and Associate Android Malware
- 8.21 Micro-Virtualization Memory Tracing to Detect and Prevent Spraying Attacks
- 8.22 Practical Memory Checking With Dr. Memory
- 8.23 Evaluating the Effectiveness of Current Anti-ROP Defenses
- 8.24 How to Make ASLR Win the Clone Wars: Runtime Re-Randomization